Coursera

Creating Advanced Reports with SAS Visual Analytics (Coursera)

Offered by SAS,
Creating Advanced Reports with SAS Visual Analytics (Coursera)

In this course, you learn how to create advanced data items, filters, and parameters in SAS Visual Analytics. What you will learn : how to create advanced data items (like calculated items and aggregated measures) in SAS Visual Analytics; how to create advanced static and interactive filters and advanced ranks in SAS Visual Analytics; how to create and apply parameters to make reports more dynamic in SAS Visual Analytics.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Course 5 of 5 in the SAS Visual Business Analytics Professional Certificate.

Syllabus

WEEK 1
Course Overview
In this module, you learn about the business scenario that you will follow for this course and where the files are located in SAS Viya for Learners.
Creating Advanced Data Items
In this module, you learn how to create and use advanced data items such as calculated items and aggregated measures in Visual Analytics.

WEEK 2
Creating Advanced Filters
In this module, you learn how to create advanced static and interactive filters in Visual Analytics.
Using Parameters to Create Advanced Reports
In this module, you learn how to use parameters in Visual Analytics to make your reports more dynamic.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Machine Learning for Data Analysis (Coursera) Coursera
Wesleyan University

Machine Learning for Data Analysis (Coursera)

Statistics & Data Analysis Data Science

Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering.

Sep 7th 2026
4 Weeks
Python Machine Learning Data Analysis
Details
Understanding Clinical Research: Behind the Statistics (Coursera) Coursera
University of Cape Town

Understanding Clinical Research: Behind the Statistics (Coursera)

Health & Society Statistics & Data Analysis

If you’ve ever skipped over`the results section of a medical paper because terms like “confidence interval” or “p-value” go over your head, then you’re in the right place. You may be a clinical practitioner reading research articles to keep up-to-date with developments in your field or a medical student wondering how to approach your own research. Greater confidence in understanding statistical analysis and the results can benefit both working professionals and those undertaking research themselves.

Sep 28th 2026
5-12 Weeks
Health Statistics Clinical Research
Details
Basic Statistics (Coursera) Coursera
University of Amsterdam

Basic Statistics (Coursera)

Statistics & Data Analysis Data Science

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression.

Sep 28th 2026
5-12 Weeks
Statistics Probability Regression
Details
Dealing With Missing Data (Coursera) Coursera
University of Maryland, College Park

Dealing With Missing Data (Coursera)

Statistics & Data Analysis Data Science

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®.

Sep 7th 2026
4 Weeks
Data Analysis Data Collection SAS
Details
Secure Your Data at Rest (Coursera) Coursera
Microsoft

Secure Your Data at Rest (Coursera)

CS: Information & Technology

Secure Your Data at Rest is the fifth course in the Microsoft Azure Security Engineer Associate Professional Certificate training program. This course teaches storage security, data sovereignty, database monitoring, encryption, data masking, and using Defender for Cloud for advanced threat protection. You must secure data at rest as this will safeguard sensitive information, prevent unauthorized access, meet regulatory compliance, and ensure data confidentiality and integrity.

Aug 31st 2026
5-12 Weeks
Encryption Azure SQL Database SAS
Details
Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera) Coursera
Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera)

Statistics & Data Analysis Data Science

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: a basic understanding of linear algebra and multivariate calculus; a basic understanding of statistics and regression models; at least a little familiarity with proof based mathematics; basic knowledge of the R programming language.

Sep 28th 2026
4 Weeks
Algebra Linear Algebra Data Science
Details
The Unix Workbench (Coursera) Coursera
Johns Hopkins University

The Unix Workbench (Coursera)

Data Science

Unix forms a foundation that is often very helpful for accomplishing other goals you might have for you and your computer, whether that goal is running a business, writing a book, curing disease, or creating the next great app. The means to these goals are sometimes carried out by writing software. Software can’t be mined out of the ground, nor can software seeds be planted in spring to harvest by autumn. Software isn’t produced in factories on an assembly line. Software is a hand-made, often bespoke good. If a software developer is an artisan, then Unix is their workbench.

Sep 28th 2026
4 Weeks
Programming Unix Machine Learning
Details
Research Data Management and Sharing (Coursera) Coursera
University of Edinburgh,University of North Carolina

Research Data Management and Sharing (Coursera)

Statistics & Data Analysis Data Science

This course will provide learners with an introduction to research data management and sharing. After completing this course, learners will understand the diversity of data and their management needs across the research data lifecycle, be able to identify the components of good data management plans, and be familiar with best practices for working with data including the organization, documentation, and storage and security of data. Learners will also understand the impetus and importance of archiving and sharing data as well as how to assess the trustworthiness of repositories.

Sep 28th 2026
5-12 Weeks
Data Management Research Research Data
Details